LLM-assisted example-based spatial search - Yip, Gerald Wei Yong (Nanyang Technological University, 2023)
This research paper presents a novel approach to search interfaces by introducing alternative example-based spatial search interfaces. Traditional search engines have significantly impacted how we retrieve information, offering efficient query-based results. However, these interfaces often rely on text-based queries and standard filtering conditions, limiting their adaptability across diverse domains. This research addresses this limitation by proposing an example-based search interface that allows users to specify queries through examples closely mirroring their desired results. While previous studies have explored alternative search methods, little attention has been given to example-based interfaces. Drawing inspiration from existing studies that have explored alternative search experiences, this research extends the concept to the realm of example-based searches. The proposed interface is tailored for spatial queries, catering to scenarios such as locating ideal vacation spots using various marker points composing the example. The fundamental premise involves users providing examples that encapsulate their search intent, enabling the system to retrieve relevant spatial information to mimic the example given. The research done contributes to the field by demonstrating the development and evaluation of an example-based spatial search interface, titled GeoMatch. GeoMatch addresses the limitations of traditional text-based methods by proposing alternative search interface designs including a natural language search interface. This research opens avenues for enhanced user experiences and improved information retrieval across various domains outside of spatial queries.